HONORS 365 - Cyberscience: Computational Science and the Rise of the Fourth Paradigm
Section: 001
Term: FA 2017
Subject: Honors Program (HONORS)
Department: LSA Honors
Credits:
3
Requirements & Distribution:
BS, NS, QR/2
Other:
Honors
Waitlist Capacity:
unlimited
Advisory Prerequisites:
Computing language course (e.g., EECS 183, 280, ENGR 101), Introductory statistics (e.g., Stats 250).
BS:
This course counts toward the 60 credits of math/science required for a Bachelor of Science degree.
Repeatability:
May not be repeated for credit.
Primary Instructor:

The course serves as a practical introduction to data science with application to the natural, social and life sciences.

In the late 20th century, the role of computation in the sciences grew rapidly, driven by advances in silicon processors, fiber-optic networks, a host of numerical algorithms, and sets of standard protocols for processing and exchanging data. These digital technologies now permeate everyday life. Building on this continuing stream of innovation, the 21st century is poised to unleash a new, data-intensive paradigm of scientific discovery that will dramatically enhance the scope and scale of data analysis from experiments, observations and simulations. This new (4th) paradigm of science is empowered by the union of computational science, statistical methods and domain science (e.g., astronomy, bioengineering, public policy). This course will invite students to explore the development and current state of computing for the sciences. Through a selection of readings, discussions with invited guests, and hands-on experimentation, students will learn about the people, practices and technologies that underlie modern scientific inquiry and gain an appreciation of the opportunities and challenges posed by the fast-growing, interdisciplinary subject of data science.

Course Requirements:

The course elements are as follows:

  • participation (10%),
  • quiz grades (20%),
  • posts and comments on the course blog (20%),
  • individual midterm paper (20%),
  • term group project written and oral presentation (30%).

    Quizzes are mainly based on weekly readings that average roughly 100 pages per week, but some are quantitative.

    Posts on the course blog (http://umichhon352fall13.wordpress.com) involve topics that are initially assigned but become open to student choice as the term progresses.

    Midterm papers focus on researching and explaining data analysis or simulation methodologies within a domain chosen by the student.

    Grading is based on thesis quality, clarity of writing, and quality and quantity of sources. For the term project, students work in groups to analyze statistical relationships between perceived easiness and quality reported for professors and subjects on the RateMyProfessor website. A special area of focus is the difference between STEM and non-STEM courses.

    Intended Audience:

    The intended audience is those students interested in the new undergraduate information degree in SI and the existing flavors of informatics major in LSA.

    Class Format:

    Through a selection of readings, discussions with invited guests, and hands on experimentation, students in the course will learn about the people, practices and technologies that underlie modern scientific inquiry and gain an appreciation of the opportunities and challenges posed by this. There is also a week-long coding lab involving generation and analysis of discrete pairwise data drawn from a two-dimensional Gaussian probability distribution function

  • HONORS 365 - Cyberscience: Computational Science and the Rise of the Fourth Paradigm
    Schedule Listing
    001 (LEC)
    P
    30921
    Closed
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    TuTh 10:00AM - 11:30AM
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